Abstract
Abstract. We propose a pipeline for the detection as well as modeling of individual buildings based on multi-source images. It allows to consistently reconstruct whole buildings at Level of Detail 3 (LoD3): the roof from airborne images and the facades including elements such as windows and doors mainly from terrestrial images. We employ a parametrized top-down model – the “shell model” – with the roof as well as the facades semantically and geometrically integrated. This generative model fosters stability for building detection by enabling the use of multi-source data and offers flexibility in modeling by means of a fully CAD-compatible integration of building components. Experiments performed on imagery from different terrestrial and airborne (Unmanned Aerial Vehicle – UAV) cameras demonstrate the potential of the approach.
Highlights
The approaches of the last decade include (Sampath, Shan, 2010), which segments and reconstructs complicated buildings from airborne LiDAR (Light Detection And Ranging) point clouds using polyhedral models. (Lafarge et al, 2010) presents building reconstruction from a Digital Surface Model (DSM) combining generic and parametric methods
In (Li et al, 2019), the point cloud is segmented using a Triangulated Irregular Network (TIN) and the boundaries of roofs are refined on a 2D grid
(Partovi et al, 2015) presents an extension of a hybrid framework for data from stereo satellite imagery with ridge-linebased building mask decomposition. (Tutzauer, Haala, 2015) is concerned with 3D facade reconstruction based on point clouds derived from mobile mapping systems and oblique airborne cameras
Summary
The approaches of the last decade include (Sampath, Shan, 2010), which segments and reconstructs complicated buildings from airborne LiDAR (Light Detection And Ranging) point clouds using polyhedral models. (Lafarge et al, 2010) presents building reconstruction from a Digital Surface Model (DSM) combining generic and parametric methods. High-resolution terrestrial images of the facades are complemented by UAV imagery taken from slightly larger distances using nadir and oblique views, with a clear view on the ground and the roofs While this opens up a possibility for direct LoD3 building modeling, we face new challenges concerning effective fusion and utilization of the data, i.e., the semantic and geometric integration of the roof and the facades as well as the facade elements including windows and doors. To this end, we employ the “shell model”, a generative statistical model for LoD3 building reconstruction based on the fusion of terrestrial and UAV imagery.
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